AI IN THE CLASSROOM: BUILDING DIGITAL READINESS FOR FUTURE BUSINESS LEADERS

Authors

  • Divyesh Kumar Jyothy Institute of Commerce and Management, Bengaluru https://orcid.org/0000-0003-3636-1441
  • S Sathyeshwar Jyothy Institute of Commerce and Management, Bengaluru

DOI:

https://doi.org/10.59415/mjacs.297

Keywords:

AI Literacy, Management Education, Student Attitudes, Digital Preparedness

Abstract

In today’s digital era, Artificial Intelligence (AI) has moved from being a distant idea to becoming a key requirement, especially in management education. As AI technologies increasingly influence business operations and decision-making, it is essential for future managers to develop AI literacy and confidence in applying these tools. This study explores AI literacy among management students, with a focus on their awareness, attitudes, and adoption behaviours.

Adopting a quantitative approach, survey data were collected from 228 undergraduate and postgraduate management students in selected business schools of Karnataka. Results from the Kruskal–Wallis test showed significant differences in AI awareness across academic specializations, indicating uneven levels of exposure. Correlation analysis identified a strong positive link between students’ attitudes toward AI and their views on its usefulness in managerial work. In addition, multiple regression analysis revealed that AI adoption in academic tasks is significantly influenced by students’ self-efficacy, prior training, and exposure to AI tools.

These findings highlight the need for curriculum reforms that enhance AI confidence, encourage cross-disciplinary learning, and integrate practical tool use. The study adds to the growing discussion on digital readiness in management education and offers practical recommendations for educators, institutions, and policymakers aiming to equip students for AI-enabled business environments.

Downloads

Download data is not yet available.

Author Biography

S Sathyeshwar, Jyothy Institute of Commerce and Management, Bengaluru

Principal, Jyothy Institute of Commerce and Management, Bengaluru

References

Alkaissi, H., & McFarlane, M. (2023). Hallucination in generative AI: Risks and trust. [Journal Name]. [URL]

Allen, L. K., & Kendeou, P. (2024). ED AI Lit: An interdisciplinary framework for AI literacy in education. [Journal Name]. https://doi.org/10.1177/23727322231220339 DOI: https://doi.org/10.1177/23727322231220339

Carolus, A., Koch, M., Straka, S., Latoschik, M. E., & Wienrich, C. (2023). MAILS—Meta AI Literacy Scale. arXiv. https://doi.org/10.48550/arXiv.2302.09319

Cetindamar, D., et al. (2024). Exploring students’ AI literacy and its effects on output quality. Smart Learning Environments. https://doi.org/10.1186/s40561-025-00384-3

Chatterjee, S., Rana, N. P., Tamilmani, K., Sharma, A., & Dwivedi, Y. K. (2021). The adoption of artificial intelligence in higher education: A systematic literature review. International Journal of Information Management, 60, 102–109. https://doi.org/10.1016/j.ijinfomgt.2021.102109

Dwivedi, Y. K., Hughes, D. L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002 DOI: https://doi.org/10.1016/j.ijinfomgt.2019.08.002

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson Prentice Hall. https://www.pearson.com/en-us/subject-catalog/p/multivariate-data-analysis/P200000003507/9780138132637

Liu, X., et al. (2025). Exploring factors influencing adoption of AI by university teachers. BMC Psychology, 13, 311. https://doi.org/10.1186/s40359-025-02620-4

Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. A. (2019). Investigating the effects of Big Data Analytics capabilities on firm performance: The mediating role of dynamic capabilities. Information & Management, 56(8), 103207. https://doi.org/10.1016/j.im.2019.05.003 DOI: https://doi.org/10.1016/j.im.2019.05.003

Ng, H. N. K. (2024). Fostering students’ AI literacy development through educational games. Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.13009 DOI: https://doi.org/10.1111/jcal.13009

Ng, H. N. K., Lee, H., et al. (2021b). [Title]. [Journal]. [URL]

Salvagno, G., et al. (2025). How AI literacy and self regulated learning relate to writing and well being. Behavioral Sciences. https://doi.org/10.3390/bs15050705

Shahzad, M. F., Xu, S., & Javed, I. (2024). ChatGPT awareness, acceptance, and adoption: Role of trust. International Journal of Educational Technology in Higher Education, 21, 46. https://doi.org/10.1186/s41239-024-00478-x DOI: https://doi.org/10.1186/s41239-024-00478-x

Shamir, A., & Levin, I. (2021–2022). AI literacy: motivation and self efficacy improve via gamified modules. [Journal]. [URL]

Shi, J., Liu, W., & Hu, K. (2025). Exploring how AI literacy and SRL relate to writing performance and well being in GenAI supported writing. Behavioral Sciences, 15(5), 705. https://doi.org/10.3390/bs15050705 DOI: https://doi.org/10.3390/bs15050705

Sima, L., et al. (2020). AI literacy: Importance in daily life and work. [Journal]. [URL]

Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson Education. https://www.pearson.com/store/p/using-multivariate-statistics/P100000581498

Wang, Y., et al. (2023). AI literacy: Application and output quality in higher education. Smart Learning Environments. https://doi.org/10.1186/s40561-025-00384-3 DOI: https://doi.org/10.1186/s40561-025-00384-3

Zhang, B., & Dafoe, A. (2019). Artificial intelligence: American attitudes and trends. Center for the Governance of AI, Future of Humanity Institute, University of Oxford. https://governance.ai/files/AI%20Attitudes%20and%20Trends%202019.pdf DOI: https://doi.org/10.2139/ssrn.3312874

Zhang, T., & Hou, J. (2025). Subjective norms and behavioral intention in AI adoption. BMC Psychology. https://doi.org/10.1186/s40359-025-02620-4 DOI: https://doi.org/10.1186/s40359-025-02620-4

Downloads

Published

2026-01-10

How to Cite

Divyesh Kumar, & S Sathyeshwar. (2026). AI IN THE CLASSROOM: BUILDING DIGITAL READINESS FOR FUTURE BUSINESS LEADERS. MLAC Journal for Arts, Commerce and Sciences (m-JACS) ISSN: 2584-1920, 4(5), 15–24. https://doi.org/10.59415/mjacs.297

ARK